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From Prompt Injections to Protocol Exploits: Threats in LLM ...

arXiv 2025-06-30 indirect prompt injection Critical

Executive Summary

An arXiv paper describes a 'Toxic Agent Flow' attack against the GitHub MCP server, using malicious GitHub issues to hijack a user's agent and leak private repository data.

What Happened

This paper describes a 'Toxic Agent Flow' attack against the GitHub MCP server. The attack uses malicious GitHub issues to hijack a user's agent and leak private repository data.

Affected Products

  • GitHub MCP server

Vulnerability / Attack Technique

Prompt injection via issues through an MCP server

Technical Mechanism

The agent reads a malicious issue through the MCP server and follows instructions to expose private repo data.

AI Security Category

LLM01:2025 Prompt Injection

Part of the Prompt Injection topic.

Part of the MCP Security topic.

Relevant Frameworks

LLM01:2025 Prompt InjectionLLM02:2025 Sensitive Information DisclosureLLM03:2025 Supply Chain

RealGround Analysis

MCP servers bring public content into private contexts. RealGround analysis: scope MCP tokens so agents reading public issues cannot reach private repos.

Recommended Controls

  • Scope GitHub MCP tokens per repository
  • Treat issue content as untrusted

Related RealGround Service

Secure AI Agent Build · or start with the free AI Agent Security Scanner.

Sources

arXiv: https://arxiv.org/html/2506.23260v1

Summary and analysis written by RealGround from the source above; last updated 2026-10-18.

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